Preliminary Draft – Topics Subject to Revision Summer Quarter Image Science Course Outline I. Foundations of Imaging Science (July 7 – August 8, 2008) Week 1: Introduction, Human Visual System, Photometry/Radiometry, Basic Statistics Week 2: Optics, Sensors, Parametric Statistical Methods Week 3: Image Processing, Introduction to Color Measurement Week 4: Displays and Output, Image Evaluation, Psychophysics Week 5: Experimental Design, Collaborative Investigations, Wrap-up II. Advanced Topics in Imaging Science (not offered summer 2008) Week 6: System Characterization for Digital Camera Systems Week 7: Flash and Shutters, Advanced Optics, Color Science I Week 8: Color Science II, Vision, Perception and JND’s; Statistical Process Control Week 9: Image Quality Prediction, Advanced Image Processing Week 10: Video and other Imaging Applications, Collaborative Project; Course Review Textbooks: The Science of Imaging, Sakby Statistics: [Rickmers & Todd equivalent] Handouts, course-supplied materials References: Handbook of Image Quality, Keelan Color Science, Wyszecki & Stiles Billmeyer and Saltzman’s Principles of Color Technology, Burns Seeing the Light, Falk, Brill, Stork Contrast Sensitivity of the Human Eye and its Effects on Image Quality, Barten Prerequisites: One year of college-level algebra and trigonometry required, Calculus helpful One year of college-level Physics Basic software programming skills (knowledge of Matlab or IDL helpful) Knowledge of photographic principles or interest to learn April 24, 2008 Preliminary Draft – Topics Subject to Revision Labs (1st Five Weeks): Characterizing HVS / contrast sensitivity / Eye Resolution Measuring Light / Statistical Variability / Field “uniformity” Optical Image Formation / Magnification, Resolution, MTF, Distortion Detectors and Response / sensitivity and noise Statistics of samples and populations (determining differences in mean, sigma) Grayscale adjustments via image processing; histograms and eye response Color measurement, reproduction and variability (create custom color test chart) Display calibration, hardcopy WYSIWYG considerations Objective performance characterization (SFR, dynamic range, SNR, sensitivity) Softcopy ruler experiment, JND’s Week-long team project (TBD) Labs (2nd Five Weeks): Spatial, Tonal, Spectral, Noise Characterizations (CIPA, Imatest, DxO, IE) Lens CRA measurements Flare (VGI, stray light) and Blemish measurements Spectral color measurements, CCT, blackbodies Subjective image quality assessments (color uniformity, sharpness, exposure) Statistical analysis of previously collected image quality data Analysis of lens performance – incoming inspection (MTF/thru focus/yield) Image processing affects on Image Quality (texture smoothing vs. sharpness) Developing a simple autofocus optimization scheme via histogram analysis Determining minimum image requirements for OCR Multispectral imaging with filters and specialized detectors Final team project (last week of course) - TBD April 24, 2008 Preliminary Draft – Topics Subject to Revision Detailed Course Syllabus – Fundamentals of Image Science Introduction: The imaging chain; sources, objects, reflectance, optics, sensors, image processing, color balancing, compression, display, visual evaluation, environment Basic Statistics: mean, variance, histograms, normal curves and the area under them, hypothesis tests, test statistics, Student’s T distribution, alpha/beta risk Human Visual System: Perception, log vs. linear response; rods/cones, photopic vs. scotopic, contrast sensitivity function, angular resolution of eye Lab: Characterizing HVS / Contrast Sensitivity / Eye Resolution Photometry/Radiometry: Energy calculations and units, solid angles, flux, intensity, illuminance, inverse-square law, exposure equations, light sources (daylight, fluorescent, incandescent, xenon flash), filters – interference vs. absorptive, IR rejection, color balancing and ND filters Lab: Measuring Light / Statistical Variability / Field “uniformity” Geometrical Optics: principles of image formation – object and image distance, magnification, focal length, f/number, hyperfocal distance, depth of field, field of view, distortion Lab: Optical Image Formation / Magnification, Resolution, MTF, Distortion Sensors: Imaging principles and characteristics of film, CCD’s and CMOS sensors; sensitivity (spectral and integrated), ISO speed calculations, SNR measurements, dynamic range & OECF, CMOS micro-lenses and Chief Ray Angle (CRA) matching, Bayer and other CFA configurations, tonal transfer Lab: Detectors and Response / sensitivity and noise Parametric Statistics: Computation of confidence intervals, estimates of population statistics from samples, hypothesis tests for variance, Chi-Square distribution, regression, correlation coefficients Lab: Statistics of samples and populations (determining differences in mean, sigma) Image Processing: Spatial, tonal, spectral, noise adjustments (sharpening, exposure compensation, color balancing). “In-camera” adjustments: Auto-exposure, auto-whitebalance, anti-vignetting. Lab: Grayscale adjustments via image processing; histograms and eye response Introduction to Color: Radiation systems and color mixing, defining, describing, and measuring color; assessing color reproduction “accuracy” and preference; introduction to color systems and spaces (CIELab, RGB, Yuv, sRGB, etc.) Lab: Color measurement, reproduction and variability (create custom color test chart) April 24, 2008 Preliminary Draft – Topics Subject to Revision Displays and Output: Softcopy display types and characteristics, hardcopy reproduction; resolution and color characteristics; calibration Lab: Display calibration, hardcopy WYSIWYG considerations, absolute color reproduction Psychophysics: Subjective evaluation approaches (paired comparisons, rank order, quality ruler, etc.); Image Quality Circle; perceptual “nesses”, psychometric scaling approaches, linking objective and subjective characteristics; introduction to JND’s Lab: Softcopy ruler experiment, JND’s Experimental Design: Choosing factors and response variable(s), experimental planning (randomization, samples sizes, etc.), factorial experiments, ANOVA, Guage R&R; application of parametric and nonparametric approaches; development Lab: Week-long Capstone team project (TBD) Detailed Course Syllabus – Advanced Topics in Imaging Science Week 6: System Characterization for Camera Systems: Tone Reproduction, Spatial Performance, Noise; sampling theory, Nyquist limit, pixel sizes vs. performance, spatial frequency response (SFR), tonal transfer, low light and exposure time, image blur; “High Dynamic Range” imaging, types of noise and assessment (noise power, etc.) Labs: Spatial, Tonal, Spectral, Noise Characterizations (CIPA, Imatest, DxO, IE) Week 7: Flash and Shutters – characterization of exposure; Advanced Optics; PSF, MTF, understanding lens design output, measuring aberrations and blemishes, optical image stabilization, autofocus and zoom lenses; Color Science I: spectral characterization Lab: Lens CRA measurements or Calculating Flash Guide Numbers Lab: Flare (VGI, stray light) and Blemish measurements Lab: Spectral color measurements, CCT, blackbody Week 8: Color science II – specifying color reproduction, color space transformations, CIE diagram, white points, color perception and adaptation; Vision and JND’s, perceptual evaluations; Statistical Process Control, control charts, sampling plans, six-sigma methodology and terms Lab: Spectral color measurements, CCT, blackbody Lab: Subjective image quality assessments (color uniformity, sharpness, exposure) Lab: Statistical analysis of Week 6 image quality data Lab: 6-Sigma analysis of lens performance – incoming inspection April 24, 2008 Preliminary Draft – Topics Subject to Revision Week 9: Image Quality Prediction: SQF, SQRI, Specifications and ISO standards; Advanced Image Processing (compression methods, artifact removal, simulations, texture smoothing, “Extended depth of Field (EDOF)” and computational imaging (DxO, Dblur, CDM optics, etc.)) Lab: Image processing affects on Image Quality (texture smoothing vs. sharpness) Lab: Developing a simple autofocus optimization scheme via histogram analysis Lab: Determining minimum image requirements for OCR Week 10: Video; Quality assessment, standard vs. HD formats, test methods; Survey of Other Imaging Applications; Multispectral systems, radiology, thermal imaging, etc., Collaborative Project; Course Review Lab: Multispectral imaging with filters and specialized detectors Lab: Collaborative team project (TBD) April 24, 2008